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Author(s): Heli Juottonen, Mirkka Kieman, Hannu Fritze, Leena Hamberg, Anna M. Laine, Päivi 
Merilä, Krista Peltoniemi, Anuliina Putkinen & Eeva-Stiina Tuittila 
Title: Integrating Decomposers, Methane-Cycling Microbes and Ecosystem Carbon Fluxes 
Along a Peatland Successional Gradient in a Land Uplift Region 
Year: 2021 
Version: Published version 
Copyright:   The Author(s) 2021 
Rights: CC BY 4.0 
Rights url: http://creativecommons.org/licenses/by/4.0/ 
 
Please cite the original version: 
Juottonen, H., Kieman, M., Fritze, H. et al. Integrating Decomposers, Methane-Cycling Microbes 
and Ecosystem Carbon Fluxes Along a Peatland Successional Gradient in a Land Uplift Region. 
Ecosystems (2021). https://doi.org/10.1007/s10021-021-00713-w 
Integrating Decomposers, Methane-
Cycling Microbes and Ecosystem
Carbon Fluxes Along a Peatland
Successional Gradient in a Land
Uplift Region
Heli Juottonen,1,2* Mirkka Kieman,3 Hannu Fritze,4 Leena Hamberg,4
Anna M. Laine,3,5,6 Pa¨ivi Merila¨,7 Krista Peltoniemi,4
Anuliina Putkinen,2,8,9 and Eeva-Stiina Tuittila3,6
1Department of Biological and Environmental Science, University of Jyva¨skyla¨, P.O. Box 35, 40014 Jyva¨skyla¨, Finland; 2Department of
Biosciences, General Microbiology, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland; 3Peatland Ecology Group, Depart-
ment of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 Helsinki, Finland; 4Natural Resources Institute Finland (Luke),
P.O. Box 2, 00791 Helsinki, Finland; 5Present Address: Geological Survey of Finland, Neulaniementie 5, P.O. Box 1237, 70211 Kuopio,
Finland; 6Present Address: School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland; 7Natural
Resources Institute Finland (Luke), Paavo Havaksen tie 3, 90570 Oulu, Finland; 8Environmental Soil Science, Department of Agri-
culture, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland; 9Institute of Atmospheric and Earth System Research (INAR)/
Forest Sciences, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland
ABSTRACT
Peatlands are carbon dioxide (CO2) sinks that, in
parallel, release methane (CH4). The peatland car-
bon (C) balance depends on the interplay of
decomposer and CH4-cycling microbes, vegetation,
and environmental conditions. These interactions
are susceptible to the changes that occur along a
successional gradient from vascular plant-domi-
nated systems to Sphagnum moss-dominated sys-
tems. Changes similar to this succession are
predicted to occur from climate change. Here, we
investigated how microbial and plant communities
are interlinked with each other and with ecosystem
C cycling along a successional gradient on a boreal
land uplift coast. The gradient ranged from shore-
line to meadows and fens, and further to bogs.
Potential microbial activity (aerobic CO2 produc-
tion; CH4 production and oxidation) and biomass
were greatest in the early successional meadows,
although their communities of aerobic decom-
posers (fungi, actinobacteria), methanogens, and
methanotrophs did not differ from the older fens.
Instead, the functional microbial communities
shifted at the fen–bog transition concurrent with a
sudden decrease in C fluxes. The successional pat-
terns of decomposer versus CH4-cycling commu-
nities diverged at the bog stage, indicating strong
but distinct microbial responses to Sphagnum
dominance and acidity. We highlight young
meadows as dynamic sites with the greatest
microbial potential for C release. These hot spots of
C turnover with dense sedge cover may represent a
Received 5 May 2021; accepted 16 September 2021
Supplementary Information: The online version contains supple-
mentary material available at https://doi.org/10.1007/s10021-021-0071
3-w.
EST and HF conceived the study; EST, PM and AML performed field
sampling and flux measurements; MK, HJ, KP and AP performed research
in the lab; LH, MK, AML and HJ analyzed data; HJ, MK, HF, AML, LH and
EST wrote the paper and all authors commented on it.
*Corresponding author; e-mail: heli.juottonen@alumni.helsinki.fi
Ecosystems
https://doi.org/10.1007/s10021-021-00713-w
 2021 The Author(s)
sensitive bottleneck in succession, which is neces-
sary for eventual long-term peat accumulation. The
distinctive microbes in bogs could serve as indica-
tors of the C sink function in restoration measures
that aim to stabilize the C in the peat.
Key words: ecosystem respiration; methane
emission; fungi; actinobacteria; methanogens;
methanotrophs; microbial biomass; microbial
community; primary paludification; peatland
development.
HIGHLIGHTS
 Early successional meadows were hot spots of
microbial activity and carbon turnover.
 Microbial community shifted at the fen–bog
transition with decreasing carbon flux.
 Microbes in bogs could be indicators for the
carbon sink function of a peatland.
INTRODUCTION
About 30% of the global soil carbon (C) is stored in
peatlands (Gorham 1991). Consequently, peatland
ecosystems play a key role in controlling atmo-
spheric carbon dioxide (CO2) and methane (CH4)
concentrations (Yu 2012). They are unique habitats
of largely water-logged organic soils, where chan-
ges in environmental conditions affect the interplay
of primary producers and decomposers, which can
turn the system into a C sink or source (for
example, Laiho 2006). This interplay includes
plants, fungi, bacteria, and CH4-producing archaea
(methanogens) and CH4-oxidizing bacteria (MOB)
especially, which are present under specific envi-
ronmental conditions that are determined by
moisture content and fertility level (Sottocornola
and others 2009; Andersen and others 2011, 2013).
Climate change is likely to disrupt the complex
interplay that determines the peatland C balance.
In peatlands, the impacts of warming are expected
to be coupled with drying due to increased evapo-
ration (Roulet and others 1992; Monier and others
2013; Helbig and others 2020). Warming and dry-
ing are advantageous for the activity of most
decomposers, thereby increasing the rates of min-
eralization (for example, Dieleman and others
2016). In addition, the community composition
responds to environmental changes: vascular plants
have an advantage over Sphagnum mosses in war-
mer and drier conditions (Weltzin and others 2000;
Breeuwer and others 2009; Dieleman and others
2015). The community response of fungi, acti-
nobacteria, methanogens, and MOB to warming
and drying appears to depend on peatland fertility
(Jaatinen and others 2005; Peltoniemi and others
2009, 2015, 2016; Urbanova´ and Ba´rta 2016). Such
community changes have been linked with alter-
ations in several ecosystem functions, such as de-
creased C accumulation (Riutta and others 2007;
Bragazza and others 2016; Laine and others 2019b)
and increased decomposition of organic matter
(Strakova´ and others 2012). In general, drying
appears to have a stronger impact on peatland
communities and functions than warming (Pel-
toniemi and others 2016; Ma¨kiranta and others
2018; Laine and others 2019a, 2019b). Although
the responses of individual communities (plants or
microbes) to environmental changes have been
studied to some extent, very few studies have
linked the concurrent responses of multiple com-
munities to ecosystem functions, such as CO2 and
CH4 exchange (however, see Jassey and others
2013, 2018; Robroek and others 2015).
Northern peatlands are dynamic systems that
typically have undergone succession from vascular-
dominated to Sphagnum moss-dominated systems
during their development (for example, Bauer and
others 2003). Similar rapid directional change has
been reported as a response to altered hydrology as
part of climate change (Gunnarsson and others
2002; Tahvanainen 2011). Concurrent with the
plant community, the microbial communities also
undergo successional change (Merila¨ and others
2006; Putkinen and others 2014). Peatland primary
succession leads to changes in ecosystem functions,
such as CO2 and CH4 exchange (Leppa¨la¨ and others
2008, 2011a, 2011b). Primary succession gradients
make it possible to assess how tightly the different
communities are linked and to predict changes in
microbial composition based on the change in plant
community structure. Peatland chronosequences at
land uplift coasts (Glaser and others 2004; Tuittila
and others 2013; Harris and others 2020; Laine and
others 2021) offer excellent settings to study how
the community changes are interlinked with
ecosystem functions, as communities and functions
can be studied under similar climatic and weather
conditions.
The aim of this study was (1) to quantify how
successional patterns in different functional groups
(plants, fungi, actinobacteria, methanogens, MOB)
are interlinked, and (2) to link the change in
communities with the change in ecosystem func-
tions (CO2 production potential, CH4 production
H. Juottonen and others
and oxidation potential, ecosystem respiration, CH4
emissions). We expected that as broad groups of
aerobic litter decomposers, fungi and actinobacteria
succession would closely follow that of vegetation
because litter type appears to be a more important
determinant of fungal and actinobacterial com-
munities in boreal peatlands than hydrology (Pel-
toniemi and others 2009, 2012). Methanogens and
MOB, on the other hand, were expected to follow
the position of the water level (WL), which controls
the aeration of the peat (Urbanova´ and others
2011; Yrja¨la¨ and others 2011), as well as the
prevalence of sedges and Sphagnum mosses, which
are substrate sources and habitats for CH4-cycling
microbes, respectively (Stro¨m and others 2003;
Putkinen and others 2014).
MATERIALS AND METHODS
Study Sites
The study area is located on the Finnish coast of the
Gulf of Bothnia (64 45¢ N, 24 42¢ E), where new
land is exposed from the sea due to post-glacial
isostatic rising. On a 10-km transect that extends
from the shore inland, the sites comprise seven
near natural peatlands (SJ0–SJ6), with successional
stages that ranged from the onset of primary peat
formation to a bog stage, which is considered as the
final stage of succession (Table 1, Figure S1). The
early stages (SJ0–SJ2) have a rather flat surface,
while in the later stages (SJ3–SJ6) the peatland
surface is patterned by microforms (dry raised
hummocks, intermediate lawns, wet flarks with
peat surface at or below water level (WL)). Typical
microforms were lawns (Sphagnum covered) and
flarks in SJ3 and SJ4, hummocks, lawns and flarks
in SJ5, and shrubby hummocks, hummocks, and
lawns in SJ6.
Field Measurements
From June to September 2007, CH4 and CO2 fluxes
(ecosystem respiration, RE) were measured at
weekly to biweekly intervals from 54 permanent
sample plots (0.56 m 9 0.56 m) established to
cover the site-specific variation in vegetation (Ta-
bles 1 and S1). Gas fluxes were measured with the
static chamber method (see supplementary mate-
rial for details). Water level and peat temperature
at 5, 10, and 20 cm depths were measured close to
each plot during the flux measurements. Plant
species cover was inventoried from the same plots
at the end of July 2007 (Table S1). Percentage
cover of vascular and moss species was estimated
visually using the scale 0.25, 0.5, 1, 2, 3–100%.
Peat Sampling and Physicochemical
Analyses
In August 2007, we collected two parallel sets of
soil cores (one for microbiological and one for
physicochemical analysis) with a box sampler
(8 9 8 9 100 cm) or with a cylinder sampler
(4.5 cm diameter, 50 cm length) from each site
along the transect. The cores were taken within
2 m of each gas flux sample plot from areas with
similar vegetation to avoid disturbance on the plots.
In addition to the sites with gas flux measurements
(SJ0–SJ6), we took four cores from the sandy
submerged littoral zone (SJm1) near SJ0 to repre-
sent the soil before the land was exposed.
Table 1. Characteristics of Successional Stages Along the Peatland Gradient
Site Successional
stage
Terrestrial age
(y)a
Peat thickness
(cm)a
Typical vegetation Number of sample
plots
SJm1 Under the sea
level
0 0 Phragmites 4
SJ0 Exposed shore 70 0 Grasses 6
SJ1 Epilobium mea-
dow
100–180 £ 10 Grasses, sedges, brown mosses 6
SJ2 Equisetum mea-
dow
150–200 £ 10 Grasses, sedges, brown mosses 6
SJ3 Mesotrophic fen 500–700 50 Sedges, Sphagnum sp. 10
SJ4 Oligotrophic fen 1070 ± 70 75 Sedges, shrubs, Sphagnum sp. 9
SJ5 Fen–bog transi-
tion
2520 ± 50 180 Sedges, shrubs, Sphagnum sp., S.
fuscum
8
SJ6 Bog  3000 170–230 Shrubs, S. fuscum 9
aThe values for terrestrial age and peat thickness are summarized from Merila¨ and others (2006) and Leppa¨la¨ and others (2008).
Microbes and C Fluxes in Peatland Succession
The sampling procedure covered the variation in
moisture and vegetation typical of each site. The
cores (n = 58), which reached depths of 30, 45, or
60 cm, were cut at even intervals (10, 15, or
20 cm) resulting in three peat layers: uppermost,
middle, and deepest layer (174 samples in total).
The length of the interval depended on the peat
depth and WL: longer sections were used for sites
with deeper peat and WL. Varying the interval
(that is, thickness of the three peat layers) allowed
us to cover the peat above, around and below WL
at each site despite their widely different peat
depths (Table 1). Portions of the samples were used
for measuring pH (soil:water 1:5 v/v) and to
determine the potential rates of CO2 and CH4
production and CH4 oxidation. The remainder of
the samples were frozen (- 20 C) for molecular
and phospholipid fatty acid (PLFA) analyses. Par-
allel volumetric soil cores were used to determine
bulk density, organic matter (OM; loss in weight on
ignition, 500 C, 4 h), and total C and nitrogen (N;
LECO CHN-2000 analyzer). Results were calculated
by volume based on the bulk density of the volu-
metric sample slices (g dm-3).
Potential CO2 Production, CH4
Production, and CH4 Oxidation
Potential activity measurements for the three peat
layers (uppermost, middle, deepest) were carried
out in 120-ml flasks with 15 ml of peat (see sup-
plementary material for further details). The flasks
for CH4 production contained 30 ml of water and
were flushed with nitrogen. The flasks for CH4
oxidation received 100 ll of CH4 as substrate. The
flasks were incubated at 15 C in the dark for
4 days (CH4 production) or 1–2 days (CO2 pro-
duction and CH4 oxidation). Gas concentrations
were followed by gas chromatography as described
in Perkio¨ma¨ki and Fritze (2002; aerobic CO2 pro-
duction), Jaatinen and others (2005; CH4 oxida-
tion), and Merila¨ and others (2006; CH4
production). Production or oxidation rates were
calculated from the slope of the linear regression of
gas concentration change over time. The rates are
given per sample volume (mg or lg dm-3 h-1).
Phospholipid Fatty Acid (PLFA)
Analysis
Fungal and bacterial biomass was analyzed by
quantifying PLFAs from 1.5 to 4 g wet weight of
peat or 4–6 g wet weight of mineral soil (Frostega˚rd
and others 1993; Jaatinen and others 2007). Rela-
tive fungal abundance (F-PLFA) was quantified
from the amount of PLFA 18:2x6 (Frostega˚rd and
Ba˚a˚th 1996; Kaiser and others 2010). The sum of
twelve PLFAs (i15:0, a15:0, 15:0, i16:0, 16:1x9,
16:1x7t, i17:0, a17:0, 17:0, cy17:0, 18:1x7 and
cy19:0) was considered to represent bacterial
abundance (B-PLFA) (Frostega˚rd and Ba˚a˚th 1996).
PLFAs 10Me17 and 10Me18 were considered to
represent actinobacteria (Act-PLFA) (Kroppenstedt
1985). The quantity of the PLFAs was determined
in relation to the sample volume (lmol dm-3) by
calculating the results per dry weight (lmol g-1)
and multiplying with the sample-specific bulk
density (g dm-3).
Molecular Analyses of Microbial Groups
Total DNA was extracted from the soil with a Power
Soil DNA extraction kit (MoBio Laboratories, Inc.,
Carlsbad, CA, USA). Fungi were amplified with
primers ITS1F and ITS2 for the internal transcribed
spacer region (Gardes and Bruns 1993). Acti-
nobacterial primers were S-C-Act-0235-a-S-20 and
S-C-Act-0878-a-A-19 for actinobacterial 16S ribo-
somal RNA gene (Stach and others 2003). Type II
methanotrophs (tII-MOB) were detected with pri-
mers A189f and A621r (Holmes and others 1995;
Tuomivirta and others 2009) for methanotroph-
specific pmoA gene for particulate methane
monooxygenase. Methanogens were detected with
the primers of Luton and others (2002) that am-
plify methanogen-specific mcrA gene for methyl-
coenzyme M reductase. Fungal, actinobacterial,
and type II MOB communities were analyzed by
denaturing gradient gel electrophoresis (DGGE)
and sequencing of DGGE bands. Methanogens
were analyzed by terminal fragment length poly-
morphism (T-RFLP) and sequencing of clones. The
details of PCR, DGGE, and T-RFLP are described in
the supplementary material. The DGGE banding
patterns of fungi, actinobacteria, and tII-MOB were
compiled into presence-absence matrices. DGGE
bands with divergent mobility were considered as
operational taxonomic units (OTUs). For metha-
nogens, T-RFs of different lengths were considered
as OTUs and relative peak areas were used as rel-
ative abundances. The OTUs that appeared at least
twice in a dataset were included in the community
composition data. To determine taxonomic affilia-
tions, we constructed phylogenetic trees of DGGE
band sequences (fungi, actinobacteria, tII-MOB)
and clone sequences (methanogens; see supple-
mentary material for details). DNA sequences were
submitted to the European Nucleotide Archive
under accession numbers LN681001-LN681094
(fungi), LN681095-LN681133 (actinobacteria),
H. Juottonen and others
LN681148-LN681172 (tII-MOB), and LR999478-
LR999518 and HG993108-HG993123 (methano-
gens).
Statistical Analyses
The effects of soil properties on potential microbial
activities and biomass were investigated using
generalized additive mixed models (GAMMs) in
package mgcv with function gamm (Wood 2006) in
R (v. 3.1.1, R Core Team 2014). Normal distribu-
tion was assumed but response variables were log-
transformed when needed to achieve normality.
All sample plots in SJ0–SJ6 were included in the
analyses (n = 54). Models were estimated sepa-
rately for each soil layer. Because many of the
variables that describe soil properties were strongly
correlated (Table S2), only the most important
(that is, WL, OM, and pH) were included in the
models. Water level, as the mean of the measure-
ments up to the sampling date, was included in the
model as a categorical variable with values 0 (the
vertical middle point of a sample below the mean
WL) and 1 (the vertical middle point of a sample
above the mean WL). We considered this an
acceptable estimation of the differences in the
moisture conditions at a rather small spatial scale
(Figure S2). Organic matter and pH were smoothed
when the models were estimated. In addition to
these fixed effect variables, site was included as a
random factor in the models. Response curves were
drawn based on GAMMs using mean values for the
other explanatory variables rather than those of
interest in the models.
Global non-metric multidimensional scaling
(GNMDS) was performed for the vegetation and
each microbial group to investigate changes in
these communities along the successional gradient,
using the vegan package (v. 2.3-0, Oksanen and
others 2015) in R. The Bray–Curtis dissimilarity
measure was used for vegetation (cover data),
Raup–Crick for fungi, actinobacteria and tII-MOB
(binary data), and Gower for methanogens (nu-
meric data). Separate MetaMDS runs were per-
formed 50 times to ensure the best possible solution
(that is, to avoid local optima). The solution with
the lowest stress value was chosen. Environmental
variables were fitted using permutation tests. Spe-
cies that occurred in at least in five samples were
drawn to species ordination figures. The effect of
successional stage and peat layer on microbial
communities was tested with permutational anal-
ysis of variance (PERMANOVA) (Anderson 2001)
with the function adonis2 in the vegan package.
Procrustes analysis with the functions procrustes
and protest in the vegan package based on the first
four NMDS dimensions was used to compare the
successional patterns of different functional groups
(Peres-Neto and Jackson 2001; Lisboa and others
2014). The Procrustes analysis between vegetation
and microbial groups only included the uppermost
and middle layers to focus on the layers influenced
by the surface vegetation. The analyses between
microbial groups included all layers. The distance
measures in PERMANOVA and Procrustes analysis
were the same as in GNMDS. Finally, we used the
Procrustes residuals to compare the strength of
correlation among microbial groups along the
peatland succession (Lisboa and others 2014). Dif-
ferences between successional stages were deter-
mined with analysis of variance and Tukey’s post
hoc tests.
RESULTS
Vegetation, Soil Chemical Variables, Gas
Fluxes and Microbial Biomass Along
the Peatland Succession
Along the successional gradient, total vegetation
cover increased from < 20% in recently exposed
shore SJ0 to nearly 150% in bog SJ6 (Figure 1a,
Table S3). From the fen SJ3 onward, the increasing
vegetation cover was due to the increase in shrubs
(Figure 1b) and Sphagnum mosses (Figure 1c).
Sedge cover was highest in the fen SJ3. Organic
matter density tripled from meadow SJ2 to fen SJ3,
indicating the start of peat accumulation (Fig-
ure 1f). Although OM, C, and N densities were
greatest in the fen sites SJ3 and SJ4, C:N increased
throughout the gradient (SJ0–SJ6) (Figure 1g).
Acidity increased along the gradient from pH 6.1 in
SJ0 to 4.2. in SJ6 (Figure 1e). Water level was
lowest in the bog SJ6 (Figure 1e).
Ecosystem respiration peaked in fen SJ3 (Fig-
ure 1d). CH4 emissions showed rather similar levels
in sites SJ1–SJ5 and were lowest at the end points
of the gradient (Figure 1d). The greatest microbial
activity potential, as indicated by the rates of aer-
obic CO2 and anaerobic CH4 production, was
measured at the meadow sites, especially SJ2
(Figure 1h). In contrast, potential CH4 oxidation
increased from SJ0 to SJ2 and then remained at
this elevated level along the whole gradient. Fun-
gal, bacterial, and actinobacterial biomass peaked
in the meadow sites and were greatest in SJ2. The
ratio of fungi to bacteria (F:B) was greatest in the
oldest sites SJ5 and SJ6 (Figure 1i).
Microbes and C Fluxes in Peatland Succession
Within-Site Variation in Relation
to Microform and Peat Layer
To capture the pronounced vertical variation and
horizontal patterning typical of boreal peatlands,
our sampling strategy covered three peat layers and
the different microforms in the stages where
microforms were present. The young meadow sites
SJ0–SJ2 showed no horizontal patterns of vegeta-
tion cover, C fluxes, soil properties, or microbial
variables. These sites had a thin organic surface
layer that covered the mineral soil (Table 1). Ver-
tically, this layer showed the greatest CO2 and CH4
production and CH4 oxidation rates and microbial
biomass at these sites (Table S4). In the older sites
SJ3–SJ6 with thicker peat layer and microforms,
the cover of Sphagnum mosses and shrubs was
greater in drier microforms (lawns in SJ3 and SJ4,
hummocks in SJ5 and SJ6) (Table S5). Microform-
related variation in RE was low, whereas CH4
emissions were generally greater in the moister
microforms within the sites SJ3–SJ6. Potential CO2
production in the older sites did not vary with
depth or microform. Potential CH4 production in
SJ3–SJ6 was generally greater below WL and in the
moister microforms (Tables S4–S6). CH4 oxidation
rates were generally greater below the uppermost
layer, especially in the drier microforms. Fungal
Figure 1. Variables describing peatland succession (SJ0–SJ6) with land uplift from the sea (SJm1): a–c plant functional
type cover, d ecosystem respiration (RE) and methane (CH4) emissions, e–g water level (WL) and soil properties, h
potential rates of carbon dioxide (CO2) (aerobic) and CH4 production and CH4 oxidation, and i microbial biomass: B-PLFA,
bacterial phospholipid fatty acids (PLFAs); F-PLFA, fungal PLFAs; Act-PLFA, actinobacterial PLFAs; F:B is the ratio of
fungal to bacterial PLFAs. Values are site means including three peat layers (SJm1 n = 12; SJ0–SJ2 n = 18; SJ3 n = 30; SJ4
n = 27: SJ5 n = 24; SJ6 n = 27). To fit the scale, F:B and CH4 emissions are presented 100 times larger, organic matter
(OM) and nitrogen (N) 10 times larger, and CO2 production 10 times smaller than the initial values.
H. Juottonen and others
biomass decreased with depth in SJ3–SJ6, whereas
bacterial and actinobacterial biomass were mainly
greatest in the middle layer (Table S6).
Relationship of Microbial Activity
Potentials to Soil Variables Based
on Generalized Additive Mixed Models
(GAMMs)
Potential CO2 production increased with increasing
OM density in all layers (Figure 2a–c). In the
middle layer, CO2 production leveled at an OM
density of about 70 g dm-3 and greater (Fig-
ure 2b). The deepest layer showed greater CO2
production when the layer was above the WL
(Figure 2c). Similarly, potential CH4 production
was affected by the position of the WL (Figure 2d–
f). In the surface layer, CH4 production increased
with higher pH (> 5) but only when the layer was
below the WL (Figure 2d). In the middle layer,
none of the selected soil properties explained the
CH4 production rate, with the possible exception of
WL (p = 0.059). In the deepest layer, only a weak
link was observed between CH4 production and
increasing OM density, but only if this layer was
above the WL (Figure 2f). The response of potential
CH4 oxidation depended on the peat layer. In the
surface layer, CH4 oxidation increased with
increasing OM density, especially under the WL
and at pH 5 (Figure 2g). In the middle layer, CH4
Figure 2. Effects of water level (WL), organic matter (OM) density, and pH on the microbial activity potentials (aerobic
CO2 production, CH4 production, and oxidation) for three peat layers. Sites SJ0–SJ6 were included in the model for each
layer (n = 54). Response curves were drawn based on generalized additive mixed models (GAMMs) so that explanatory
variables other than the presented variable were retained as their mean value. The effects of OM and pH are presented
only when p < 0.05. All effects of the WL categories (above, below) are shown (p values in bold when p < 0.05). Empty
subfigure e had no significant soil properties. In figures d–i: black denotes OM density; gray denotes pH. Note the different
axis scales. R2adj. = adjusted R
2 value of the model.
Microbes and C Fluxes in Peatland Succession
oxidation varied strongly with OM density and
peaked at an OM density of about 50 g dm-3
(Figure 2h). In the deepest layer, CH4 oxidation
was accentuated, especially above the WL, by
increasing acidity and OM (Figure 2i).
Plant and Microbial Communities Along
the Peatland Gradient
Vegetation formed a clear gradient from SJ0 to SJ6
(Figure 3); from grass- to sedge-dominated com-
munities, and finally to Sphagnum-dominated veg-
etation (including dwarf shrubs). Bulk density, pH,
C:N, and the cover of Sphagnum and shrubs showed
the greatest correlation (r ‡ 0.74) with plant com-
munity change (Table S7). Overall microbial com-
munity structure based on PLFAs showed a similar,
though less differentiated, successional gradient
and separated the young meadows (SJ1, SJ2), mid-
successional fens (SJ3, SJ4), and the oldest bog sites
(SJ5, SJ6) from each other (Figure 4). At the level
of microbial functional groups, successional stage
explained a larger proportion of community vari-
ation than peat layer for all the groups (Table 2).
The community structure of fungi, actinobacteria,
and methanogens showed a common pattern
where the late stages (SJ5, SJ6) were separated
from the other stages, and the early (SJ0–SJ2) and
mid-successional (SJ3, SJ4) stages were grouped
together (Figure 5a–i, Figure S3). Methanotrophs
were not detected in the youngest sites (SJ0, SJ1).
The tII-MOB community in the oldest sites (SJ5,
SJ6) was separated from the younger sites, but tII-
MOB also differed more clearly with peat layer
than the other groups (Figure 5j–l). Changes in the
fungal, actinobacterial, and tII-MOB communities
correlated best with C:N, pH and the cover of
Sphagnum and shrubs, and the methanogen com-
munities with C, N, and OM density and Sphagnum
cover (Table S8). We used Procrustes analysis,
which superimposes two ordinations, to compare
the successional patterns of vegetation and micro-
bial functional groups. Fungal community showed
the greatest correlation with vegetation composi-
tion, and actinobacteria the lowest (Table 2). When
comparing the successional patterns of the different
functional groups, the strongest correlations were
seen between actinobacteria and fungi, and be-
tween actinobacteria and methanogens, and lowest
between methanogens and tII-MOB (Table 2).
Procrustes residuals showed a fairly uniform cor-
relation of actinobacteria vs. fungi and methano-
gens vs. tII-MOB along the gradient (Figure 6).
Procrustes residuals of actinobacteria and fungi
with CH4-cycling microbes increased toward the
bog sites, particularly the oldest site SJ6, indicating
decreasing correlation of community patterns.
Phylogenetic Affiliation of the Microbial
Groups
The majority of fungal sequences clustered with
Ascomycota and Pezizomycotina, including genera
Penicillium (SJ0), Articulospora (SJ0, SJ1, SJ4),
Figure 3. Global non-metric multidimensional scaling (GNMDS) ordination of a vegetation in sites SJ0–SJ6, and b plant
species scores. Ovals represent 95% confidence intervals. The vectors in a represent environmental variables with
correlation ‡ 0.5.
H. Juottonen and others
Phialocephala (SJ2), Venturia (SJ2, SJ4), Rhizocyphus
(SJ5, SJ6), and Archaerhizomyces (SJ6) (Figure S4).
Approximately 25% of the sequences clustered with
Basidiomycota and the order Agaricales, but the
genera varied with successional stage. The majority
of actinobacterial 16S rRNA gene sequences clus-
tered with Mycobacteriaceae (SJm1–SJ6), Ther-
momonosporaceae (SJ0–SJ6), or Acidimicrobiaceae
(SJm1–SJ6) (Figure S5). All the tII-MOB pmoA se-
quences clustered with the alphaproteobacterial
genus Methylocystis and showed strong similarity to
sequences from peatlands (Figure S6). The most
common methanogens along the gradient, based
on mcrA clone sequences from sites SJm1, SJ2, SJ3,
and SJ5, were Methanobacteriaceae (SJ2, SJ5),
Methanoflorentaceae (SJ3), Methanoregulaceae
(SJm1, SJ2, SJ5), Methanosarcinaceae (SJm1, SJ5)
Methanothrichaceae (SJm1, SJ2, SJ3), Methanomas-
siliicoccales (SJ3, SJ5), and Methanomicrobiaceae
(SJm1) (Figure S7).
DISCUSSION
Comparison of the Successional Patterns
of Functional Groups
In this study, we were interested to determine how
the community changes of litter decomposers and
CH4 cycling microbes are coupled along a peatland
successional gradient, and how the changes relate
to ecosystem processes in C cycling. This is the first
study that integrates all these components along a
peatland succession, which ranges from recently
exposed shoreline to meadows, young fens, and
finally bogs. The succession was evidenced as
decreasing pH, increasing OM accumulation and
C:N, as seen in primary succession gradients (Pen-
nanen and others 2001; Tscherko and others 2003),
and as the increasing Sphagnum cover and peat
thickness, characteristic of peatland succession
(Korhola 1992; Hughes and Dumayne-Peaty 2002).
Vegetation and the overall microbial community
(based on PLFAs) changed gradually along the
gradient. At the level of functional microbial
Figure 4. Global non-metric multidimensional scaling (GNMDS) ordination of phospholipid fatty acid (PLFA) results
showing a sites SJ0–SJ6, b three peat layers with lines connecting the layers of each site, and c correlations ‡ 0.5 of
environmental factors and PLFA summary variables with the ordination.
Table 2. Effect of Successional Stage and Peat Layer on Vegetation and Microbial Groups and Correlations of
Community Compositions
Group PERMANOVAb R2 Procrustes R
Stage Layer Actinobacteria Fungi tII-MOB Methanogens
Vegetation 0.53 – 0.33 0.64 0.52 0.54
Actinobacteria 0.45 0.17 – – – –
Fungi 0.37 0.25 0.60 – – –
tII-MOBa 0.38 0.13 0.45 0.44 – –
Methanogens 0.55 0.12 0.58 0.54 0.40 –
p = 0.001 for all.
aType II methanotrophs.
bPermutational multivariate analysis of variance.
Microbes and C Fluxes in Peatland Succession
Figure 5. Global non-metric multidimensional scaling (GNMDS) ordination of communities and individual operational
taxonomic units (OTUs) for fungi (a–c), actinobacteria (d–f), methanogens (g–i), and tII-MOB (j–l) in sites SJ0–SJ6. The
vectors represent environmental variables with correlation ‡ 0.5, except for ecosystem respiration (RE), methane (CH4)
emissions, and distance to WL ‡ 0.4. Correlations of vectors are presented in Table S8 and layer-wise ordinations in
Figure S3.
H. Juottonen and others
groups, a common feature in the successional pat-
terns of aerobic decomposers (fungi, actinobacte-
ria), methanogens and, to some extent,
methanotrophs was that the bog sites (SJ5, SJ6)
showed distinct communities, rather than a gradual
change. The oldest bog SJ6 also showed a decou-
pling of aerobic decomposer versus CH4-cycling
communities, whereas the coupling between fungi
versus actinobacteria, and tII-MOB versus metha-
nogens was similar to the rest of the gradient. Bogs
represent the climax stage of peatland succession
where the low pH and abundant cover of Sphagnum
with its chemical composition have an adverse ef-
fect on other organisms (van Breemen 1995) and
constitute environmental filtering that is expected
to structure the microbial communities (Medvedeff
and others 2015; Ivanova and others 2020; Juot-
tonen 2020; St. James and others 2021).
Against our expectation that actinobacterial and
fungal communities (as plant litter degraders)
would show greater correlation with vegetation
composition than the CH4-cycling groups, only
fungi followed this prediction. However, acti-
nobacteria and fungi correlated strongly with each
other, suggesting similar drivers along the gradient.
The more pronounced drivers for both actinobac-
teria and fungi were acidity and Sphagnum moss
cover, which were strongly interlinked (Laine and
others 2021), and the cover of shrubs. Fungi form
mycorrhizae with shrubs (Smith and Read 2008),
and actinobacteria inhabit the shrub rhizosphere
(Aanderud and others 2008). Such associations
may explain the particularly strong correlation
observed here between these microbes and shrubs.
Accordingly, ectomycorrhizal Lactarius and Russula
(Basidiomycetes) were detected in bog SJ6 with the
greatest shrub cover. Shrub cover and acidity may
also explain the presence of Archaeorhizomycetes
in bog SJ6, because these fungi are considered root-
associated fungi that favor high C content and
acidity (Rosling and others 2013; Carrino-Kyker
and others 2016). In another potentially acidity-
driven pattern, actinobacterial Acidimicrobiaceae
from the fen and bog sites were grouped with the
acidophilic and potentially iron-cycling genera
Acidimicrobium and Aciditerrimonas (Stackebrandt
2014), whereas those from the young sites with
higher pH formed a separate cluster, suggesting
different niche preferences related to peatland
succession within Acidimicrobiaceae. Such prefer-
ences may explain why actinobacteria had similar
drivers as fungi but did not follow the gradual
vegetation change as consistently as fungi.
Methane-cycling microbes maintained a similar
level of coupling along the gradient, but overall,
the tII-MOB and methanogen communities did not
correlate strongly and, indeed, were driven by dif-
ferent factors, none of which was WL. In previous
studies, tII-MOB have followed methanogen com-
munities, presumably because methanogens pro-
duce the substrate for MOB (Yrja¨la¨ and others
2011; Juottonen and others 2012). The lack of
Figure 6. Strength of correlation of microbial functional groups determined as residuals of Procrustes analysis. tII-MOB
denotes type II methanotrophs. A small residual value indicates stronger correlation. Different letters indicate significant
differences between the successional stages at p < 0.05. Ends of whiskers represent minimum and maximum values
excluding outliers, which are shown as separate points.
Microbes and C Fluxes in Peatland Succession
connection with methanogens in this peatland
gradient with a wide range of habitats can be ex-
plained by the ability of many Methylocystis spp. to
grow facultatively (without CH4) on acetate, etha-
nol, or hydrogen (Belova and others 2010; Im and
others 2011; Hakobyan and others 2020). As ex-
pected, we found that Sphagnum cover was one of
the best explanatory factors for tII-MOB commu-
nity variation, because MOB inhabit the living
Sphagnum mosses in addition to the decomposing
peat (Kip and others 2010). The occurrence of
MOB associated with living Sphagnum differed be-
tween the younger and older successional stages in
this peatland succession gradient (Putkinen and
others 2014). Type II MOB, which our approach
targeted and which are the prevalent type of MOB
in acidic northern peatlands (Chen and others
2008; Dedysh 2011; Zhou and others 2017), were
detected in living Sphagnum throughout the gradi-
ent, whereas several type I MOB groups were
prominent in the younger sites (Putkinen and
others 2014). Such dominance of type I MOB could
explain why we did not detect tII-MOB in the
earliest seashore and meadow stages: SJm1, SJ0,
and SJ1.
Methanogens showed the strongest response to
the peatland successional gradient overall, consis-
tent with the known separation of methanogen
communities with peatland type and hydrology
(Juottonen and others 2005; Cadillo-Quiroz and
others 2006; Merila¨ and others 2006; Godin and
others 2012). The strongest detected drivers of
methanogen communities (that is, OM, C, and N
content and Sphagnum cover) were tightly linked to
the gradient. These findings suggest that metha-
nogens are sensitive microbial indicators of peat-
land succession.
Linking Microbial Community Changes
with Ecosystem Functions Along
the Peatland Gradient
The greatest potential microbial activity (aerobic
CO2 production and CH4 production and oxidation)
and RE rates appeared in the early successional
meadows and the youngest fen, although the
community structures of the functional microbial
groups in the meadows were not distinct from the
other young peatland stages. This could be ex-
pected for actinobacteria and fungi as the widely
distributed process of CO2 production cannot be
attributed to specific microbial groups. Instead, the
meadow stages exhibited the largest bacterial and
fungal biomass, which points to a strong potential
for microbial C turnover. In driving the strong
microbial activity, the younger stages show greater
levels of photosynthesis than the older stages
(Leppa¨la¨ and others 2008). The meadows had a
greater cover of sedges, which suggests the avail-
ability of root exudates to fuel microbial processes,
including methanogenesis (Stro¨m and others
2003). Meadow SJ2 with strong CH4 production
potential contained groups of methanogens asso-
ciated with sedges or with elevated CH4 production
activity levels: acetate-using Methanotrichaceae
and hydrogenotrophic Methanobacteriaceae
(Bra¨uer and others 2020).
It is surprising that all the microbial activity
potentials peaked in the young meadow sites, given
that our modeling results suggest that CO2 pro-
duction, CH4 production, and CH4 oxidation
potentials were driven by OM, acidity, and WL in
very distinct ways. However, when the microbial
biomass and pH (around 5) at these sites are con-
sidered, this was favorable for both CH4 production
and oxidation. The meadows and the youngest fen
represent dynamic environments that operate with
considerable variations in resources and conditions,
and do not possess as many limiting factors as the
older peatlands with pH < 5. We propose that
these early successional sites at the start of OM
accumulation represent the ‘Goldilocks’ zone of
peatland succession for C cycling: A sufficiently
high and stable WL, but not too wet or too
stable that allows both aerobic and anaerobic pro-
cesses and the replenishment of redox-sensitive
substrates; not too acidic; and adequate availability
of C but not so much that processes would become
N limited. This stage may act as a bottleneck for the
development of a peatland with a thick peat layer
and conditions that limit decomposition. Fen veg-
etation has been suggested as important for sup-
porting multiple C cycling functions in peatlands
(Robroek and others 2017) as the abundance of
resources and processes makes these peatlands
larger sources of CO2 and CH4 than the more
stable older sites, and their dynamism makes these
emissions sensitive to environmental changes.
Role of Peat Layers and Microforms
in Successional Patterns
Strong depth-related variation and spatial variation
complicate the comparison of peat profiles from
widely differing peatlands, such as those in the
gradient of this study. Successional changes in peat
thickness, WL, the depth distribution of peat
chemical composition, and the presence of micro-
forms along the gradient must be considered in
sampling design. First, our sampling scheme aimed
H. Juottonen and others
to obtain good spatial coverage of the different
microforms, which are known to affect microbial
communities (Galand and others 2003; Deng and
others 2013; Kotiaho and others 2013; Asema-
ninejad and others 2019). However, microform-
related variation was not evident at the community
scale along the gradient (Figure S3). Second, we
aimed to sample the peat above, around, and below
the WL in each stage. Basing sampling depths solely
on WL would have led to comparisons of microbial
communities among very different peat substrates.
It is possible that this sampling scheme, where the
thickness of the sample layer increased with peat
layer thickness, may have reduced the resolution
for methanogens and tII-MOB, which are known
to vary closer to the WL. Nonetheless, our sampling
approach represents a carefully considered com-
promise designed to allow comparison of all stages
along such an extensive peatland gradient.
CONCLUSIONS
Our study provides a comprehensive view on the
interplay of peatland vegetation, decomposer
communities, and CH4-cycling microbes in the
regulation of CO2 and CH4 production, by
addressing all these components in the same peat-
land successional gradient. The results highlight the
role of young meadows and fens as dynamic sites
sensitive to environmental changes (Leppa¨la¨ and
others 2011b), with the greatest microbial potential
for C release along the gradient. This major C
turnover phase may represent a bottleneck in
peatland succession that is necessary for peat
accumulation. The dynamics of these young sites
were not captured successfully by a peatland suc-
cessional model (Tuittila and others 2013), which
further underlines the need to understand the
controls of C cycling in young peatlands with a thin
peat layer. The concept of young peatland mead-
ows as the ‘Goldilocks’ zone of carbon cycling could
be applicable to other regions where sedge- or
grass-dominated areas start accumulating peat,
especially when thicker peat is accompanied by
increasing acidity. The considerable potential for C
turnover in the meadows was not apparent from
microbial community composition alone, stressing
the importance of measuring microbial activity and
biomass. Because the microbial communities re-
mained relatively similar throughout the meadow
and older fen stages, climate or land use changes
that increase vascular plant and sedge cover espe-
cially, could potentially turn such sites into similar
hot spots of microbial C turnover as the young fens.
On the other hand, microbial community compo-
sition across the different functional groups was an
excellent indicator of the strong restriction of C
cycling activity in bogs. The uncoupling of
decomposer and CH4-cycling communities further
indicates the strong but distinct microbial response
to Sphagnum dominance and increasing acidity and
C:N ratio. The specific microbial communities ob-
served in bogs could be used as indicators of a
peatland C sink and as a potential baseline of
restoration measures that aim to stabilize the C in
the peat. As the response stems from the unique
characteristics of Sphagnum peat, such indicators
could be useful over a wide geographical range of
Sphagnum-dominated peatlands.
ACKNOWLEDGEMENTS
We thank Hanna Aulanko, Juha Puranen, Sirpa
Tiikkainen, Julie Rodriguez, and Gilberto Duran-
Torres for assistance in the laboratory, Sanna
Ehonen, Meri Ruppel, Lauri Hirvisaari, and Mark-
ku Nikola for assistance with fieldwork, and Mirva
Leppa¨la¨ for assistance in sample processing. The
work was funded by the Academy of Finland
(Projects 131409, 218101, 315415, 287039, and
330840), funding from Kone Foundation to AML,
and funding from the Finnish Society of Forest
Science to MK.
FUNDING
Open access funding provided by University of Jy-
va¨skyla¨ (JYU).
Declarat ions
Confl ic t of interest The authors declare
that they have no conflict of interest.
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